Images produced by the Scheimpflug principle are being used to quantitate eye opacities in a study whose purpose is to evaluate the potential for the accurate evaluation of changes in cataract patients. This may provide a means of documenting and monitoring cataracts in vivo, allowing clinical trials of drugs that may prevent or reverse the cataract formation process. Statistical evaluation of our results is currently underway. In addition, we are using computer classifying and clustering methodology for automatic identification or diagnosis of cataracts. A statistical study is determining the number of views necessary to characterize different types of cataracts. A group of normal controls is being used to study the effects of aging on the lens and how opacity increases with age. Pharmaceuticals are available that may prevent or reverse the cataract formation process. A clinical trial in human patients cannot be pursued because of inadequate means of documenting and monitoring cataracts in vivo. It is hoped that our methodology will provide the statistical and image processing foundation to document and assess changes in lens opacities in cataract patients.